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Economic Theory: Structural Abstraction or Behavioral Reduction

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Economic Theory: Structural Abstraction or Behavioral Reduction Shyam Sunder Yale University History of Political Economy Conference Duke University, April 22-24, 2005 – PowerPoint PPT presentation

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Title: Economic Theory: Structural Abstraction or Behavioral Reduction


1
Economic Theory Structural Abstraction or
Behavioral Reduction
  • Shyam Sunder
  • Yale University
  • History of Political Economy Conference
  • Duke University, April 22-24, 2005

2
Outline Psychology and Reductionist Doubts
  • Physics, optimization as an organizing principle
    of nature
  • Borrowed into economics, optimization was
    gradually transformed from equilibrium
    abstraction into a behavioral principle
  • Cognitive psychology humans are not good
    intuitive optimizers noisy, imprecise, learners
  • A reductionist attitude to science expects
    derivation of aggregate outcomes from
    descriptively valid individual behavior it is
    difficult, sometimes not possible
  • The difficulty leads to doubts about the
    foundations of economic theory

3
Outline Computers Yield New Insights into
Economics
  • Computers seep into inaccessible parts of
    economics (Mirowski, 2002), transforming it in
    fundamental ways
  • Discovery the apparent mismatch between the
    cognitively bounded biological man and its
    optimizing cousin of econ texts is not
    necessarily a problem
  • A good news-bad news story
  • The Good news Economists can have their cake and
    psychologists eat it too
  • The Bad news Have to give up insistence on
    reducing economics and psychology into a single
    science
  • The unity of science movement disbanded some 60
    years ago, but is alive and thriving in
    behavioral economics
  • Each science chooses its own level of
    abstraction economic theory chose one, just as
    psychologists choose another
  • A great deal of science would be impossible if we
    insist on integrating all adjacent disciplines
    into a single logical structure

4
Computation and Economics
  • Each discipline is shaped by its tools
  • Role of mechanical and electronic computers in
    shaping economics
  • Computers may yet help shift the recent excessive
    preoccupation of economics with individual
    behavior, back to structural analysis

5
Computers and Demand
  • Lowered cost of transactions
  • Exploration of previously inaccessible
    possibilities (computational chemistry and
    biology)
  • Fixed cost of discovery allows products to stay
    in the market beyond the life of the
    discovery-enabling technology
  • Speculative demand due to knowledge of demand
    with new communication technology
  • New uses of older products and services
  • Life-style, migration and social
    organization-driven demand changes
  • Endogeneity of demand and technology

6
Computation and Markets
  • Technology has given both greater specificity as
    well as greater ambiguity to definition of
    markets
  • Specificity through the salience of hardware and
    software used to operate them
  • Ambiguity when an investor in Boston buys a
    share of stock of a firm with its headquarters in
    Cleveland, from another investor in Tokyo through
    a broker who lives in San Francisco and works for
    a Chicago brokerage house, in London Stock
    Exchange, with its hardware located in Frankfurt,
    software from Bangalore, and regulatory
    supervision of EU in Brussels, where is the
    market, and what is its extent?

7
Computers Transforming Markets
  • Organization and operation of markets
  • As traders or traders assistants
  • Science and engineering of markets

8
Organization and Operation
  • Reliable bookkeeping
  • Flexibility and accessibility of control
    information
  • Clearing and settlement
  • Reporting and dissemination of information
  • Monitoring and regulation (insider trading)
  • Risk management
  • Input of information to the markets
  • Demand for integration, legislation
  • Reorganization of markets

9
Computer as a Trader
  • Computational decision aids are ubquitous
  • Substitution exciting and controversial
  • Do human intelligence and world view define the
    outer limits of what computers can see and do?
  • Memory and speed are important components of
    intelligence. Computer programs for chess are
    already as good as the best human players. It is
    just a matter of time before

10
Tooling Up for Computational Economics
  • William Norris, Control Data, PLATO for education
    and training in 1976
  • Use of PLATO for economics experiments
  • PCs arrive
  • Modeling traders in order to
  • Identify human algorithms from trading data
  • Design new, better algorithms
  • Replace paid subjects in econ experiments
  • Economics and finance literature were of little
    help

11
Stock Market Crash of 1987
  • Blame on program trading
  • Proposal to teach a course on program trading
    (with a background research agenda)
  • Getting the platform, software, coding language
    and tools ready
  • Market 2001 (turned out to be too optimistic)
  • Show some data

12
What Makes the Difference
13
Class Experience
  • Teaching becomes learning
  • Efficiency as a measure of intellence
  • Code length and performance
  • Difficulties of identifying strategies from code
  • Not modular
  • Does a superior strategy exist?
  • Where is your strategy, Sir?

14
This Makes No Sense
  • Why did the markets populated with simple
    budget-constrained random bid/ask strategies
    converge close to Walrasian prediction in price
    and allocative efficiency
  • No memory, learning, adaptation, maximization,
    even bounded rationality
  • Intensive search for programming and system
    errors did not yield fruit
  • Modeling and analysis supported simulation
    results
  • Students versus ZI traders

15
Our Inference
  • Perhaps it is the structure, not behavior that
    accounts for the first order magnitude of
    outcomes in competitive settings
  • Computers opened a new window into a previously
    inaccessible aspect of economics
  • Ironically, it was not through computers
    celebrated optimization capability
  • Instead, through deconstruction of human behavior
  • Isolating the market level consequences of simple
    or arbitrarily chosen classes of individual
    behavior

16
Time Dimension of Demand
  • Theory largely abstracts away from the time
    dimension of demand defined as quantity per unit
    of time, with discrete periodic market clearing
    through auction
  • The difficulties of this abstraction became clear
    when Chamberlin (1948) and Smith (1962) tried to
    implement demand in lab and realized the
    difficulties
  • Most markets require price making with continual
    trading (no discrete clearing)
  • Should demand be interpreted as a steady rate of
    inflow of demand (and supply) units into the
    market with the hope that it will reach a
    (stochastic) steady state?
  • What would be the characteristics of market
    behavior?
  • Do the untraded (mostly extramarginal) units
    accumulate, or do they exit the market? When?

17
Optimization Principle
  • In physics marbles and photons behave but are
    not attributed any intention or purpose
  • Yet, optimization principle has proved to be an
    excellent guide to how physical and biological
    systems as a whole behave
  • At multiple hierarchical levels--brain, ganglion,
    and individual cellphysical placement of neural
    components appears consistent with a single,
    simple goal minimize cost of connections among
    the components. The most dramatic instance of
    this "save wire" organizing principle is reported
    for adjacencies among ganglia in the nematode
    nervous system among about 40,000,000
    alternative layout orderings, the actual ganglion
    placement in fact requires the least total
    connection length. In addition, evidence supports
    a component placement optimization hypothesis for
    positioning of individual neurons in the
    nematode, and also for positioning of mammalian
    cortical areas.
  • (Makes you wonder what went wrong with human
    design when you see all the biases and
    incompetence of human cognition.
  • Could it be just the wrong benchmark?)
  • Questions about forests and questions about
    trees

18
Optimization Principle Imported into Economics
  • Humans and human systems as objects of economic
    analysis
  • Conflict between mechanical application of
    optimization principle and our self-esteem (free
    will)
  • Optimization principle interpreted as a
    behavioral principle, shifting focus from
    aggregate to individual behavior
  • Cognitive science we are not good at optimizing
  • Increasing willingness among economists to
    abandon the optimization principle

19
Dropping the Infinite Faculties Assumption
  • Conlisk
  • Empricial evidence in favor of bounded
    rationality
  • Empirical evidence on importance of bounded
    rationality
  • Proven track record of bounded rationality models
    (in explaining individual behavior)
  • Unconvincing logic of unbounded rationality
  • All reasons focus on the trees not forest

20
Equilibrium and Simon
  • Some time in 1993, Simon came to my office, we
    sat in front of my computer and I showed him the
    pictures I showed you
  • His reaction So, there is an answer after all!
    (to the apparent contradiction between the
    discrepancy between cognitive man and its
    economic model). He was preparing the third
    edition of The Sciences of the Artificial and
    wrote
  • This skyhook-skyscraper construction of science
    from the roof down to the yet unconstructed
    foundations was possible because the behavior of
    the system at each level depended on only a very
    approximate, simplified, abstracted
    characterization of the system at the level next
    beneath. This is lucky, else the safety of
    bridges and airplanes might depend on the
    correctness of the Eightfold Way of looking at
    elementary particles.
  • Indeed, the powerful results of economic theory
    were derived from a very approximate,
    simplified, abstracted characterization of the
    system at the level next beneath,the economic
    man so maligned, and its scientific purpose and
    role so misunderstood, by many who claim to be
    followers of Simon

21
Economics Behavioral or Structural
  • Economics can be usefully thought of as a
    behavioral science in the sense physicists study
    the behavior of marbles and photons
  • Given the pride we take in attributing the
    endowment of free will to ourselves, this
    interpretation of behavior is a hard sell in
    social sciences
  • To build on the achievements of theory, it may be
    better if we think of optimization in economics
    as a structural principle
  • Just as physicists (and many biologists) do

22
Thank You
  • Please send comments to
  • Shyam.sunder_at_yale.edu
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